Removed spelling mistake (3)

Readme.md

@@ -1,6 +1,6 @@
 # Varjo Gaze Detector
 
-Varjo Gaze Detector classifies gaze events in eye-tracking recordings from the Varjo VR and XR headsets. It detects fixations, saccades, smooth persuits and blinks. As well as their duration, amplituded and mean/max velocities. 
+Varjo Gaze Detector classifies gaze events in eye-tracking recordings from the Varjo VR and XR headsets. It detects fixations, saccades, smooth pursuits and blinks. As well as their duration, amplituded and mean/max velocities. 
 This tool is developed by Thomas de Boer, with use of the detection algorithm from [sp_tool](https://github.com/MikhailStartsev/sp_tool) by Mikhail Startsev. Please cite their paper when using this code:
 
     @inproceedings{agtzidis2016smooth,
@@ -65,7 +65,7 @@ Make sure the folder structure is participant/trial as follows, if you would lik
                 varjo_gaze_output_XX-XX-XXXX.csv
 
 The detection results are saved in a 'detection' folder in each trial folder. 
-Detection and their measures are saved as fixations.csv, saccades.csv, persuits.csv and blinks.csv
+Detection and their measures are saved as fixations.csv, saccades.csv, pursuits.csv and blinks.csv
 
 # How to use
 Make sure the right packages are installed in your environment:

main.py

@@ -49,7 +49,7 @@
 # Analyzing gaze event measures --------------------------------------------------------------------------------------
         Fixations = calculators.fixation(x, y, t, e, printresults)
         Saccades  = calculators.saccade(x, y, v, t, e, printresults)
-        Persuits  = calculators.persuit(x, y, v, t, e, printresults)
+        Pursuits  = calculators.pursuit(x, y, v, t, e, printresults)
         Blinks    = calculators.blink(t, e, printresults)
 
 # Saving gaze event data ---------------------------------------------------------------------------------------------
@@ -59,16 +59,16 @@
             # save detections per even type with their measures
             functions.save_events(Fixations, 'fixations.csv', outputpath)
             functions.save_events(Saccades, 'saccades.csv', outputpath)
-            functions.save_events(Persuits, 'persuits.csv', outputpath)
+            functions.save_events(Pursuits, 'pursuits.csv', outputpath)
             functions.save_events(Blinks, 'blinks.csv', outputpath)
             # add gaze_event classification column to raw data and save copy
             csvdata = readers.file_reader(datapath, participant, trial, filename)
             csvdata["gaze_event"] = classifiedgazedata['data']['EYE_MOVEMENT_TYPE']
             csvdata.to_csv(outputpath + "/classified_data.csv")
 
 # Plotting and saving------------------------------------------------------------------------------------------------
-        plotters.detection(x, y, t, v, Fixations, Saccades, Persuits, Blinks, trials, trial, axs)
-        plotters.calculation(Fixations, Saccades, Persuits, Blinks, trial, participant)
+        plotters.detection(x, y, t, v, Fixations, Saccades, Pursuits, Blinks, trials, trial, axs)
+        plotters.calculation(Fixations, Saccades, Pursuits, Blinks, trial, participant)
         outputpath = trialpath + "calculation-p{}-t{}.png".format(participant, trial, participant, trial)
         if savefig: plt.savefig(outputpath, bbox_inches='tight')